Vertically detailed in situ measurements of gelbstoff: demonstrating the impact of a runoff event

Hydrobiologia ◽  
2004 ◽  
Vol 517 (1-3) ◽  
pp. 171-177
Author(s):  
Steven W. Effler ◽  
David M. O'Donnell ◽  
MaryGail Perkins ◽  
David G. Smith
Keyword(s):  
In Situ Measurements ◽  
Runoff Event ◽  
The Impact

scholarly journals Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

2021 ◽  
Vol 13 (10) ◽  
pp. 1927
Author(s):  
Fuqin Li ◽  
David Jupp ◽  
Thomas Schroeder ◽  
Stephen Sagar ◽  
Joshua Sixsmith ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Correction Method ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Correction Algorithm ◽  
Simple Method ◽  
North East ◽  
The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

The importance of the turbulent ship wake regime for pollutant fate and transport

2021 ◽  
Author(s):  
Amanda T. Nylund ◽  
Rickard Bensow ◽  
Mattias Liefvendahl ◽  
Arash Eslamdoost ◽  
Anders Tengberg ◽  
...  
Keyword(s):  
Fate And Transport ◽  
In Situ Measurements ◽  
Ex Situ ◽  
Landsat 8 ◽  
Turbulent Regime ◽  
Near Wake ◽  
Ship Wake ◽  
Spatiotemporal Scales ◽  
The Impact

<p>This interdisciplinary study with implications for fate and transport of pollutants from shipping, investigates the previously overlooked phenomenon of ship induced mixing. When a ship moves through water, the hull and propeller induce a long-lasting turbulent wake. Natural waters are usually stratified, and the stratification influences both the vertical and horizontal extent of the wake. The altered turbulent regime in shipping lanes governs the distribution of discharged pollutants, e.g. PAHs, metals, nutrients and non-indigenous species. The ship related pollutant load follows the trend in volumes of maritime trade, which has almost tripled since the 1980s. In heavily trafficked areas there may be one ship passage every ten minutes; today shipping constitutes a significant source of pollution.</p><p>To understand the environmental impact of shipping related pollutants, it is essential to know their fate following regional scale transport. However, previous modelling efforts assuming discharge at the surface will not adequately reflect the input values in the regional models. Therefore, it is urgent to bridge the gaps between the spatiotemporal scales from high-resolution numerical modeling of the flow hydrodynamics around the ship, mixing processes and interaction of the ship and wake with stratification, and parameterization in regional oceanographic modeling. Here this knowledge gap is addressed by combining an array of methods; in situ measurements, remote sensing and numerical flow modeling.</p><p>A bottom-mounted Acoustic Doppler Current Profiler was placed under a ship lane, for <em>in-situ</em> measurements of the vertical and temporal expansion of turbulent wakes. In addition, <em>ex-situ</em> measurements with Landsat 8 Thermal Infrared Sensor were used to estimate the longevity and spatial extent of the thermal signal from ship wakes. The computational modelling was conducted using well resolved 3D RANS modelling for the hull and the near wake (up to five ship lengths aft), a method typically used for the near wake behaviour in analysing the propulsion system. As this is not feasible to use for a far wake analysis, the predicted wake is then used as input for a 2D+time modelling for the sustained wake up to 30min after the ship passage. These results, both from measurements and numerical models, are then combined to analyse how ship-induced turbulence influence at what depth discharged pollutants will be found.</p><p>This first step to cover the mesoscales of the turbulent ship wake is necessary to assess the impact of ship related pollution. In-situ measurements show median wake depth 13.5m (max 31.5m) and median longevity 10min (max 29min). Satellite data show median thermal wake signal 13.7km (max 62.5km). A detailed simulation model will only be possible to use for the first few 100m of the ship wake, but the coupling to a simplified 2D+time modelling shows a promising potential to bridge our understanding of the impact of the ship wake on the larger scales. Our model results indicate that the natural stratification affects the distribution and retention of pollutants in the wake region. The depth of discharge and the wake turbulence characteristics will in turn affect the fate and transport of pollutants on larger spatiotemporal scales.</p>

Comparing Assimilation of Soil Moisture and C-band Backscatter in High Resolution Land Surface Model

2020 ◽  
Author(s):  
Leqiang Sun ◽  
Stéphane Belair ◽  
Marco Carrera ◽  
Bernard Bilodeau
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Open Loop ◽  
In Situ Measurements ◽  
Lookup Table ◽  
Surface Model ◽  
Loop Model ◽  
The Impact

<p>Canadian Space Agency (CSA) has recently started receiving and processing the images from the recently launched C-band RADARSAT Constellation Mission (RCM). The backscatter and soil moisture retrievals products from the previously launched RADARSAT-2 agree well with both in-situ measurements and surface soil moisture modeled with land surface model Soil, Vegetation, and Snow (SVS). RCM will provide those products at an even better spatial coverage and temporal resolution. In preparation of the potential operational application of RCM products in Canadian Meteorological Center (CMC), this paper presents the scenarios of assimilating either soil moisture retrieval or outright backscatter signal in a 100-meter resolution version of the Canadian Land Data Assimilation System (CaLDAS) on field scale with time interval of three hours. The soil moisture retrieval map was synthesized by extrapolating the regression relationship between in-situ measurements and open loop model output based on soil texture lookup table. Based on this, the backscatter map was then generated with the surface roughness retrieved from RADARSAT-2 images using a modified Integral Equation Model (IEM) model. Bias correction was applied to the Ensemble Kalman filter (EnKF) to mitigate the impact of nonlinear errors introduced by multi-sourced perturbations. Initial results show that the assimilation of backscatter is as effective as assimilating soil moisture retrievals. Compared to open loop, both can improve the analysis of surface moisture, particularly in terms of reducing bias.  </p>

Comparison of GRACE Level-3 Data with Super Conducting Gravimeters in Europe By Means of Signal Decomposition Analysis

2020 ◽  
Author(s):  
Miguel Angel Izquierdo Perez ◽  
Christian Voigt ◽  
Elmas Sinem Ince ◽  
Frank Flechtner
Keyword(s):  
Decomposition Analysis ◽  
Decomposition Methods ◽  
Component Analysis ◽  
In Situ Measurements ◽  
Alternative Methods ◽  
Earth Tides ◽  
Grace Data ◽  
The Individual ◽  
The Impact

<p>With the launch of the Gravity Recovery and Climate Experiment (GRACE) mission in 2002 and continued with GRACE Follow-on (GRACE-FO) since 2018, it is nowadays possible to monitor important mass variations in the Earth system. Nevertheless, validating these observations is a challenging task due to the lack of alternative methods to obtain directly comparable in-situ measurements. The most appropriate approach for this endeavor consists of comparing the GRACE derived Total Water Storage (TWS) residuals against Superconducting Gravimeter (SG) residuals, which provide long term stability.</p> <p>The in-situ data used for this project are the gravity residuals obtained after removing the effects of solid Earth tides and ocean tidal loading, atmospheric loading, instrumental drift, polar motion and length‐of‐day induced gravity changes, from nine SG stations between January 2010 and March 2017. Such residuals were then compared with GRACE retrieved TWS residuals obtained from the Gravity Information System (GravIS) portal (gravis.gfz-potsdam.de).</p> <p>In this project, three decomposition methods were used for the comparisons: Principal Component Analysis (PCA), Spatiotemporal Independent Component Analysis (stICA) and Multivariate Singular Spectral Analysis (MSSA). The main aim was to assess the impact of the GRACE data corrections applied by GravIS to the coefficient C20, the coefficients of degree/order one, and the Glacial Isostatic Adjustment (GIA) effect. Moreover, the Gaussian, DDK and VDK filtering techniques were evaluated as well.</p> <p>The tested methods proved to cope with the residual hydrological effects on SG measurements up to an extend that allows an objective evaluation of the data. The results obtained from this analysis indicate that the most optimal solution is achieved by correcting the C20 and degree/order 1 coefficients. The most effective filters are DDK1, VDK2 and Gaussian with a 500 km bandwidth, in that order. Furthermore, the GIA correction demonstrates to be relevant for northern locations like Onsala.</p> <p>Concerning the decomposition methods, MSSA demonstrates to be a powerful tool, synthesizing the most important common trends among the in-situ measurements of different stations, and displaying the local differences of the signals. The common signals extracted from PCA represent a good overview of the trends from the data but is not detailed at the individual locations. Finally, the stICA decomposition is not able to extract these common signals when the input data is significantly different across the individual variables for SG data. This is explained by the Blind Source Separation (BSS) nature of the methodology, which intends to identify differences among the signals, and is not useful in this case where the signals are affected by the local hydrology.</p> <p>The importance of this study lies in the versatility that the successfully tested methods show for the purpose of GRACE data comparison. Furthermore, the methodology applied in this project can be extended to analyze the current GRACE-FO mission as well other gravimetric satellite missions in the future.</p>

scholarly journals Intercomparison of Soil Moisture Retrieved from GNSS-R and from Passive L-Band Radiometry at the Valencia Anchor Station

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1900
Author(s):  
Cong Yin ◽  
Ernesto Lopez-Baeza ◽  
Manuel Martin-Neira ◽  
Roberto Fernandez-Moran ◽  
Lei Yang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Circular Polarization ◽  
European Space Agency ◽  
In Situ Measurements ◽  
Anchor Station ◽  
L Band ◽  
The Impact ◽  
Band Radiometer ◽  
Soil Moisture Monitoring

In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on the intercomparison of soil moisture monitoring from Global Navigation Satellite System Reflectometry (GNSS-R) signals and passive L-band microwave radiometer observations at the Valencia Anchor Station is introduced. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and a dual-pol down-looking antenna for receiving LHCP (left-hand circular polarization) and RHCP (right-hand circular polarization) reflected signals from the soil surface. Data were collected from the three different antennas through the two channels of Oceanpal GNSS-R receiver and, in addition, calibration was performed to reduce the impact from the differing channels. Reflectivity was thus measured, and soil moisture could be retrieved. The ESA (European Space Agency)-funded ELBARA-II (ESA L Band Radiometer II) is an L-band radiometer with two channels with 11 MHz bandwidth and respective center frequencies of 1407.5 MHz and 1419.5 MHz. The ELBARAII antenna is a large dual-mode Picket horn that is 1.4 m wide, with a length of 2.7 m with −3 dB full beam width of 12° (±6° around the antenna main direction) and a gain of 23.5 dB. By comparing GNSS-R and ELBARA-II radiometer data, a high correlation was found between the LHCP reflectivity measured by GNSS-R and the horizontal/vertical reflectivity from the radiometer (with correlation coefficients ranging from 0.83 to 0.91). Neural net fitting was used for GNSS-R soil moisture inversion, and the RMSE (Root Mean Square Error) was 0.014 m3/m3. The determination coefficient between the retrieved soil moisture and in situ measurements was R2 = 0.90 for Oceanpal and R2 = 0.65 for Elbara II, and the ubRMSE (Unbiased RMSE) were 0.0128 and 0.0734 respectively. The soil moisture retrievals by both L-band remote sensing methods show good agreement with each other, and their mutual correspondence with in-situ measurements and with rainfall was also good.

Retrieval of Stable Water Vapour Isotopologues from the TROPOMI Instrument

2021 ◽  
Author(s):  
Tim Trent ◽  
Hartmut Boesch ◽  
Peter Somkuti ◽  
Mathhias Schneider ◽  
Farahnaz Khosrawi ◽  
...  
Keyword(s):  
Water Vapour ◽  
In Situ Measurements ◽  
Climate Feedback ◽  
Retrieval Algorithm ◽  
Unique Contribution ◽  
Water Vapour Content ◽  
Infrared Measurements ◽  
Water Isotopologues ◽  
The Impact

<p>Atmospheric moisture is a crucial factor for the redistribution of heat in the atmosphere, with a strong coupling between atmospheric circulation and moisture pathways responsible most climate feedback mechanisms. Conventional satellite and in situ measurements provide information on water vapour content and vertical distribution; however, observations of water isotopologues make a unique contribution to a better understanding of this coupling.</p><p>In recent years, observations of water vapour isotopologue from satellites have become available from nadir thermal infrared measurements (TES, AIRS, IASI) which are sensitive to the free troposphere and from shortwave-infrared (SWIR) sensors (GOSAT, SCIAMACHY) that provide column-averaged concentrations including sensitivity to the boundary layer. The TROPOMI instrument on-board Sentinel 5P (S5p) measures SWIR radiance spectra that allow retrieval of water isotopologue columns but with much improved spatial and temporal coverage compared to other SWIR sensors promising a step-change for scientific and operational applications.</p><p>Here we present the retrieval algorithm development for stable water isotopologues from TROPOMI as part of the ESA S5p Innovation programme.  We also discuss the validation of these types of satellite products with fiducial in situ measurements, and challenges compared with other satellite measurements. Finally, we outline the roadmap for assessing the impact of TROPOMI data against state-of-the-art isotope enabled models.</p>

Surface temperature and radiation budget of snow-covered complex terrains

2021 ◽  
Author(s):  
Alvaro Robledano ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Fanny Larue ◽  
Inès Ollivier
Keyword(s):  
Surface Temperature ◽  
Single Channel ◽  
Spatial Variations ◽  
In Situ Measurements ◽  
Surface Energy Budget ◽  
Radiation Budget ◽  
Atmospheric Effects ◽  
Landsat 8 ◽  
The Impact

<p>The temporal evolution of the snowpack is controlled by the surface temperature, which plays a key role in physical processes such as snowmelt. It shows large spatial variations in mountainous areas, where the illumination conditions are variable and depend on the topography. The surface energy budget is affected by the particular processes that occur in these areas, such as the modulation of the illumination by local slope and the re-illumination of the surface from surrounding slopes. These topography effects are often neglected in models, considering the surface as flat and smooth. Here we aim at estimating the surface temperature and the radiation budget of snow-covered complex terrains, in order to evaluate the role of the different processes that control their spatial variations. For this, a modelling chain is implemented to derive surface temperature from in-situ measurements. The main component is the Rough Surface Ray-Tracing (RSRT) model, based on a photon transport algorithm to quantify the impact of surface roughness in snow-covered areas. It is coupled to a surface scheme in order to estimate the radiation budget. To validate the model, we use in-situ measurements and satellite thermal observations (TIRS sensor aboard Landsat-8) in the Col du Lautaret area, in the French Alps. The satellite images are corrected from atmospheric effects with a single-channel algorithm. The results of the simulations show (i) an agreement between the simulated and observed surface temperature for a diurnal cycle in winter; (ii) the spatial variations of surface temperature are on the order of 5 to 10°C between opposed slope orientations; (iii) the agreement with satellite observations is improved when considering topography effects. It is therefore necessary to account for these effects to estimate the spatial variations of the radiation budget and surface temperature over snow-covered complex terrain. </p>

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